John F. Wambaugh

Integration of Dosimetry, Exposure and High-Throughput Screening Data in Chemical Toxicity Assessment

High-throughput in vitro toxicity screening can provide an efficient way to identify potential biological targets for chemicals. However, relying on nominal assay concentrations may misrepresent potential in vivo effects of these chemicals due to differences in bioavailability, clearance, and exposure. Hepatic metabolic clearance and plasma protein binding were experimentally measured for 239 ToxCast Phase I chemicals. The experimental data were used in a population-based in vitro-to-in vivo extrapolation model to estimate the daily human oral dose, called the oral equivalent dose, necessary to produce steady-state in vivo blood concentrations equivalent to in vitro AC(50) (concentration at 50% of maximum activity) or lowest effective concentration values across more than 500 in vitro assays. The estimated steady-state oral equivalent doses associated with the in vitro assays were compared with chronic aggregate human oral exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. A total of 18 (9.9%) chemicals for which human oral exposure estimates were available had oral equivalent doses at levels equal to or less than the highest estimated U.S. population exposures. Ranking the chemicals by nominal assay concentrations would have resulted in different chemicals being prioritized. The in vitro assay endpoints with oral equivalent doses lower than the human exposure estimates included cell growth kinetics, cytokine and cytochrome P450 expression, and cytochrome P450 inhibition. The incorporation of dosimetry and exposure provide necessary context for interpretation of in vitro toxicity screening data and are important considerations in determining chemical testing priorities.

Incorporating Human Dosimetry and Exposure into High-Throughput In Vitro Toxicity Screening

Many chemicals in commerce today have undergone limited or no safety testing. To reduce the number of untested chemicals and prioritize limited testing resources, several governmental programs are using high-throughput in vitro screens for assessing chemical effects across multiple cellular pathways. In this study, metabolic clearance and plasma protein binding were experimentally measured for 35 ToxCast phase I chemicals. The experimental data were used to parameterize a population-based in vitro-to-in vivo extrapolation model for estimating the human oral equivalent dose necessary to produce a steady-state in vivo concentration equivalent to in vitro AC(50) (concentration at 50% of maximum activity) and LEC (lowest effective concentration) values from the ToxCast data. For 23 of the 35 chemicals, the range of oral equivalent doses for up to 398 ToxCast assays was compared with chronic aggregate human oral exposure estimates in order to assess whether significant in vitro bioactivity occurred within the range of maximum expected human oral exposure. Only 2 of the 35 chemicals, triclosan and pyrithiobac-sodium, had overlapping oral equivalent doses and estimated human oral exposures. Ranking by the potencies of the AC(50) and LEC values, these two chemicals would not have been at the top of a prioritization list. Integrating both dosimetry and human exposure information with the high-throughput toxicity screening efforts provides a better basis for making informed decisions on chemical testing priorities and regulatory attention. Importantly, these tools are necessary to move beyond hazard rankings to estimates of possible in vivo responses based on in vitro screens.

High-throughput models for exposure-based chemical prioritization in the ExpoCast project.

The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research program to prioritize chemical inventories for potential hazard. Similar capabilities for estimating exposure potential would support rapid risk-based prioritization for chemicals with limited information; here, we propose a framework for high-throughput exposure assessment. To demonstrate application, an analysis was conducted that predicts human exposure potential for chemicals and estimates uncertainty in these predictions by comparison to biomonitoring data. We evaluated 1936 chemicals using far-field mass balance human exposure models (USEtox and RAIDAR) and an indicator for indoor and/or consumer use. These predictions were compared to exposures inferred by Bayesian analysis from urine concentrations for 82 chemicals reported in the National Health and Nutrition Examination Survey (NHANES). Joint regression on all factors provided a calibrated consensus prediction, the variance of which serves as an empirical determination of uncertainty for prioritization on absolute exposure potential. Information on use was found to be most predictive; generally, chemicals above the limit of detection in NHANES had consumer/indoor use. Coupled with hazard HTS, exposure HTS can place risk earlier in decision processes. High-priority chemicals become targets for further data collection.

High Throughput Heuristics for Prioritizing Human Exposure to Environmental Chemicals

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the hazard presented by the chemical and the extent of exposure. However, many chemicals lack estimates of exposure intake, limiting the understanding of health risks. We aim to develop a rapid heuristic method to determine potential human exposure to chemicals for application to the thousands of chemicals with little or no exposure data. We used Bayesian methodology to infer ranges of exposure consistent with biomarkers identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We performed linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using chemical descriptors and use information from multiple databases and structure-based calculators. Five descriptors are capable of explaining roughly 50% of the variability in geometric means across 106 NHANES chemicals for all the demographic groups, including children aged 6-11. We use these descriptors to estimate human exposure to 7968 chemicals, the majority of which have no other quantitative exposure prediction. For thousands of chemicals with no other information, this approach allows forecasting of average exposure intake of environmental chemicals.

Modeling Single and Repeated Dose Pharmacokinetics of PFOA in Mice

Perfluorooctanoic acid (PFOA) displays complicated pharmacokinetics in that serum concentrations indicate long half-lives despite which steady state appears to be achieved rapidly. In this study, serum and tissue concentration time-courses were obtained for male and female CD1 mice after single, oral doses of 1 and 10 mg/kg of PFOA. When using one- and two-compartment models, the pharmacokinetics for these two dosages are not consistent with serum time-course data from female CD1 mice administered 60 mg/kg, or with serum concentrations following repeated daily doses of 20 mg/kg PFOA. Some consistency between dose regimens could be achieved using the saturable resorption model of Andersen et al. In this model PFOA is cleared from the serum into a filtrate compartment from which it is either excreted or resorbed into the serum by a process presumed transporter mediated with a Michaelis-Menten form. Maximum likelihood estimation found a transport maximum of T(m) = 860.9 (1298.3) mg/l/h and half-maximum concentration of K(T) = 0.0015 (0.0022) mg/l where the estimated standard errors (in parentheses) indicated large uncertainty. The estimated rate of flow into and out of the filtrate compartment, 0.6830 (1.0131) l/h was too large to be consistent with a biological interpretation. For these model parameters a single dose greater than 40 mg/kg, or a daily dose in excess of 5 mg/kg were necessary to observe nonlinear pharmacokinetics for PFOA in female CD1 mice. These data and modeling analyses more fully characterize PFOA in mice for purposes of estimating internal exposure for use in risk assessment.

Relative Impact of Incorporating Pharmacokinetics on Predicting In Vivo Hazard and Mode of Action From High-Throughput In Vitro Toxicity Assays

The use of high-throughput in vitro assays has been proposed to play a significant role in the future of toxicity testing. In this study, rat hepatic metabolic clearance and plasma protein binding were measured for 59 ToxCast phase I chemicals. Computational in vitro-to-in vivo extrapolation was used to estimate the daily dose in a rat, called the oral equivalent dose, which would result in steady-state in vivo blood concentrations equivalent to the AC 50 or lowest effective concentration (LEC) across more than 600 ToxCast phase I in vitro assays. Statistical classification analysis was performed using either oral equivalent doses or unadjusted AC 50 /LEC values for the in vitro assays to predict the in vivo effects of the 59 chemicals. Adjusting the in vitro assays for pharmacokinetics did not improve the ability to predict in vivo effects as either a discrete (yes or no) response or a low effect level (LEL) on a continuous dose scale. Interestingly, a comparison of the in vitro assay with the lowest oral equivalent dose with the in vivo endpoint with the lowest LEL suggested that the lowest oral equivalent dose may provide a conservative estimate of the point of departure for a chemical in a dose-response assessment. Furthermore, comparing the oral equivalent doses for the in vitro assays with the in vivo dose range that resulted in adverse effects identified more coincident in vitro assays across chemicals than expected by chance, suggesting that the approach may also be used to identify potential molecular initiating events leading to adversity.

Incorporating High-Throughput Exposure Predictions with Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast efforts expand (ie, Phase II) beyond food-use pesticides toward a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. Environmental Protection Agency (EPA) ExpoCast program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, 3 or 13 chemicals possessed AERs < 1 or < 100, respectively. Diverse bioactivities across a range of assays and concentrations were also noted across the wider chemical space surveyed. The availability of HT exposure estimation and bioactivity screening tools provides an opportunity to incorporate a risk-based strategy for use in testing prioritization.

Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring

There is a growing need in the field of exposure science for monitoring methods that rapidly screen environmental media for suspect contaminants. Measurement and analysis platforms, based on high resolution mass spectrometry (HRMS), now exist to meet this need. Here we describe results of a study that links HRMS data with exposure predictions from the U.S. EPAs ExpoCast™ program and in vitro bioassay data from the U.S. interagency Tox21 consortium. Vacuum dust samples were collected from 56 households across the U.S. as part of the American Healthy Homes Survey (AHHS). Sample extracts were analyzed using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS) with electrospray ionization. On average, approximately 2000 molecular features were identified per sample (based on accurate mass) in negative ion mode, and 3000 in positive ion mode. Exact mass, isotope distribution, and isotope spacing were used to match molecular features with a unique listing of chemical formulas extracted from EPAs Distributed Structure-Searchable Toxicity (DSSTox) database. A total of 978 DSSTox formulas were consistent with the dust LC-TOF/molecular feature data (match score≥90); these formulas mapped to 3228 possible chemicals in the database. Correct assignment of a unique chemical to a given formula required additional validation steps. Each suspect chemical was prioritized for follow-up confirmation using abundance and detection frequency results, along with exposure and bioactivity estimates from ExpoCast and Tox21, respectively. Chemicals with elevated exposure and/or toxicity potential were further examined using a mixture of 100 chemical standards. A total of 33 chemicals were confirmed present in the dust samples by formula and retention time match; nearly half of these do not appear to have been associated with house dust in the published literature. Chemical matches found in at least 10 of the 56 dust samples include Piperine, N,N-Diethyl-m-toluamide (DEET), Triclocarban, Diethyl phthalate (DEP), Propylparaben, Methylparaben, Tris(1,3-dichloro-2-propyl)phosphate (TDCPP), and Nicotine. This study demonstrates a novel suspect screening methodology to prioritize chemicals of interest for subsequent targeted analysis. The methods described here rely on strategic integration of available public resources and should be considered in future non-targeted and suspect screening assessments of environmental and biological media.

Exploring consumer exposure pathways and patterns of use for chemicals in the environment

Highlights • To assign use-related information to chemicals to help prioritize which will be given more scrutiny relative to human exposure potential.• Categorical chemical use and functional information are presented through the Chemical/Product Categories Database (CPCat).• CPCat contains information on >43,000 unique chemicals mapped to ∼800 terms categorizing their usage or function.• The CPCat database is useful for modeling and prioritizing human chemical exposures.

Simulating Microdosimetry in a Virtual Hepatic Lobule

The liver plays a key role in removing harmful chemicals from the body and is therefore often the first tissue to suffer potentially adverse consequences. To protect public health it is necessary to quantitatively estimate the risk of long-term low dose exposure to environmental pollutants. Animal testing is the primary tool for extrapolating human risk but it is fraught with uncertainty, necessitating novel alternative approaches. Our goal is to integrate in vitro liver experiments with agent-based cellular models to simulate a spatially extended hepatic lobule. Here we describe a graphical model of the sinusoidal network that efficiently simulates portal to centrilobular mass transfer in the hepatic lobule. We analyzed the effects of vascular topology and metabolism on the cell-level distribution following oral exposure to chemicals. The spatial distribution of metabolically inactive chemicals was similar across different vascular networks and a baseline well-mixed compartment. When chemicals were rapidly metabolized, concentration heterogeneity of the parent compound increased across the vascular network. As a result, our spatially extended lobule generated greater variability in dose-dependent cellular responses, in this case apoptosis, than were observed in the classical well-mixed liver or in a parallel tubes model. The mass-balanced graphical approach to modeling the hepatic lobule is computationally efficient for simulating long-term exposure, modular for incorporating complex cellular interactions, and flexible for dealing with evolving tissues.